AI-Driven Finance: From Traffic Cop to Business Enabler
Figma CFO Praveer Malani and A16Z partners discuss how AI is transforming finance from a reactive reporting function to a proactive strategic engine. Key insights include the shift from SQL-based automation to AI-native workflows, the critical importance of data integrity, and the evolving role of the CFO as a business owner rather than a gatekeeper.
The Strategic Pivot in Finance
The role of the Chief Financial Officer is undergoing a fundamental transformation, driven by the integration of artificial intelligence into core financial operations. Figma CFO Praveer Malani and A16Z partners Seema Ambel and Ivan Makarov argue that finance is shifting from a reactive, compliance-focused function to a proactive, strategic engine. This evolution is not merely about speed but about changing the nature of the work: moving from analyzing what has happened to deciding what should happen next.
From SQL to AI-Native Workflows
Historically, finance automation relied on manual SQL queries and complex data stitching, a process that was time-consuming and error-prone. Today, AI-native workflows allow teams to reconcile data across multiple systems in minutes, automate collections, and prototype products for due diligence. This shift has freed finance teams from tedious tasks, enabling them to focus on high-value activities such as strategic planning, competitive benchmarking, and business experimentation. The key unlock is not just the tool but the ability to access and interpret data in real-time, fostering a culture of daily accountability and rapid iteration.
The Human Element in AI-Driven Finance
Despite the power of AI, human judgment remains paramount. Malani emphasizes that AI should augment, not replace, critical thinking. The challenge is not generating content but ensuring its quality and relevance. Teams must develop the muscle to evaluate AI outputs, validate assumptions, and apply business context. This requires a new set of skills: intellectual curiosity, data fluency, and the ability to communicate complex insights clearly. The best finance leaders are those who can use AI to enhance their decision-making while maintaining a deep understanding of the business.
Organizational Implications
The adoption of AI in finance is reshaping organizational structures and talent strategies. Companies are seeing a surge in internal innovation, with teams building custom AI agents for specific workflows. However, this decentralized approach requires centralized governance to avoid redundancy and ensure scalability. A strong CIO or systems function is essential to harmonize these efforts and productize successful tools. Additionally, the role of the CFO is evolving to include building and managing these AI-driven systems, making the position more technical and strategic. For founders and investors, the next generation of CFOs must be business owners who can leverage AI to drive growth and efficiency, rather than just gatekeepers of financial data.
Key insights
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AI is shifting finance from a historical reporting function to a forward-looking strategic engine. Teams are no longer just reconciling past data but using AI to predict trends and drive business decisions.
Impact: This shift enables finance to become a primary driver of business growth, increasing its influence on company strategy and resource allocation.
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Data integrity is the prerequisite for effective AI adoption. Without clean, consistent data, AI tools produce unreliable results, undermining trust and efficiency.
Impact: Investing in data infrastructure before deploying AI ensures that insights are accurate and actionable, reducing the risk of costly errors.
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AI should augment human judgment, not replace it. The value of AI in finance lies in enhancing human decision-making by providing faster, more comprehensive data analysis.
Impact: This approach preserves the critical thinking and business context that AI lacks, leading to more robust and reliable financial decisions.
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Corporate development teams are using AI to prototype acquisition targets and simulate leadership feedback, accelerating due diligence and improving investment quality.
Impact: This innovation reduces the time and cost of M&A processes, allowing companies to move faster and make more informed strategic decisions.
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Decentralized AI experimentation requires centralized governance to avoid redundancy and ensure scalability. A strong CIO or systems function is essential to harmonize and productize successful AI tools.
Impact: This balance between innovation and governance ensures that AI adoption is efficient, scalable, and aligned with broader business goals.
Action items
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Audit and clean your data infrastructure before deploying AI tools. Ensure that data is consistent, accessible, and accurate to maximize the value of AI-driven insights.
Impact: This foundational step prevents the amplification of data errors and ensures that AI outputs are reliable and actionable.
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Train finance teams to use AI as a decision-support tool, emphasizing the importance of human judgment and business context in interpreting AI outputs.
Impact: This enhances the quality of financial decisions and fosters a culture of critical thinking and accountability.
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Implement AI-driven prototyping and simulation in corporate development processes to accelerate due diligence and improve investment quality.
Impact: This reduces the time and cost of M&A processes, enabling faster and more informed strategic decisions.
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Establish a centralized CIO or systems function to harmonize and productize successful AI tools developed by decentralized teams.
Impact: This prevents redundancy, ensures scalability, and aligns AI adoption with broader business goals.
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Redefine the CFO role to include building and managing AI-driven systems, focusing on strategic enablement rather than just compliance and reporting.
Impact: This positions finance as a primary driver of business growth and increases its influence on company strategy.
Quotes
“I think we're going to be able to attract and build the world's best finance organization because so much of what people want is the ability to learn and feel like they're being invested in and surrounded by people that want to go and become the best at their craft.”
“You want to use AI as a tool to help you and empower you, but it's really, really critical to still be that thinker.”
“If our business complexity was staying the same, I think we probably wouldn't need the same number of people a year from now.”